Advances in neurobiology permit neuroscientists to manipulate specific brain molecules, neurons and systems. This has lead to major advances in the neuroscience of reward. Here, it is argued that further advances will require equal sophistication in parsing reward into its specific psychological components: (1) learning (including explicit and implicit knowledge produced by associative conditio...

Reward and novelty are potent learning signals that critically rely on dopaminergic midbrain responses. Recent findings suggest that although reward and novelty are likely to interact, both functions may be subserved by distinct neuronal clusters. We used high-resolution functional magnetic resonance imaging (fMRI) to isolate neural responses to reward and novelty within the human substantia ni...

Recent research indicates that reward-based motivation impacts medial temporal lobe (MTL) encoding processes, leading to enhanced memory for rewarded events. In particular, previous functional magnetic resonance imaging (fMRI) studies of motivated learning have shown that MTL activation is greater for highly rewarded events, with the degree of reward-related activation enhancement tracking the ...

Delayed rewards lose their value for economic decisions and constitute weaker reinforcers for learning. Temporal discounting of reward value already occurs within a few seconds in animals, which allows investigations of the underlying neurophysiological mechanisms. However, it is difficult to relate these mechanisms to human discounting behavior, which is usually studied over days and months an...

Several behaviours associated with anorexia nervosa (AN) are hypothesised to be highly salient and rewarding for these people (e.g., food restriction, weight-loss, and driven exercise). Neurobiological and psychophysiological evidence support a role for altered dopaminergic reward processes in the aetiology of AN and in the valued nature of its symptomatology. More specifically, preliminary dat...

The optimal reward function associated with the so-called "multiarmed bandit problem" for general Markov-Feller processes is considered. It is shown that this optimal reward function has a simple expression (product form) in terms of individual stopping problems, without any smoothness properties of the optimal reward function neither for the global problem nor for the individual stopping probl...

In this paper, we consider the model that the information on the rewards in vector-valued Markov decision processes includes imprecision or ambiguity. The fuzzy reward model is analyzed as follows: The fuzzy reward is represented by the fuzzy set on the multi-dimensional Euclidian space R and the infinite horizon fuzzy expected discounted reward(FEDR) from any stationary policy is characterized...

The application of fuzzy set theory to renewal reward processes is proposed in this paper. The reward is modeled as a fuzzy random variable. A theorem which presents the long-run average fuzzy reward per unit time is stated. A procedure to obtain the best T-age replacement policy with fuzzy cost structure is developed. The original problem is transformed into a nonlinear program in order to eva...

Abstract. The article is devoted to second order optimality in Markov decision processes. Attention is primarily focused on the reward variance for discounted models and undiscounted transient models (i.e. where the spectral radius of the transition probability matrix is less then unity). Considering the second order optimality criteria means that in the class of policies maximizing (or minimiz...